263-5806-00L  Digital Humans

SemesterSpring Semester 2023
LecturersS. Coros, S. Tang
Periodicityyearly recurring course
Language of instructionEnglish
CommentPreviously Computational Models of Motion and Virtual Humans



Courses

NumberTitleHoursLecturers
263-5806-00 VDigital Humans3 hrs
Wed14:15-16:00HG E 1.2 »
Thu10:15-11:00CAB G 61 »
S. Coros, S. Tang
263-5806-00 UDigital Humans2 hrs
Thu16:15-18:00ETF E 1 »
S. Coros, S. Tang
263-5806-00 ADigital Humans2 hrsS. Coros, S. Tang

Catalogue data

AbstractThis course covers the core technologies required to model and simulate motions for digital humans and robotic characters. Topics include kinematic modeling, physics-based simulation, trajectory optimization, reinforcement learning, feedback control for motor skills, motion capture, data-driven motion synthesis, and ML-based generative models. They will be richly illustrated with examples.
ObjectiveStudents will learn how to estimate human pose, shape, and motion from videos and create basic human avatars from various visual inputs. Students will also learn how to represent and algorithmically generate motions for digital characters and their real-life robotic counterparts. The lectures are accompanied by four programming assignments (written in python or C++) and a capstone project.

The deadline to cancel/deregister from the course is May 1st. Deregistration after the deadline will lead to fail.
Content- Basic concept of 3D representations
- Human body/hand models
- Human motion capture;
- Non-​rigid surface tracking and reconstruction
- Neural rendering
- Optimal control and trajectory optimization
- Physics-based modeling for multibody systems
- Forward and inverse kinematics
- Rigging and keyframing
- Reinforcement learning for locomotion
Prerequisites / NoticeExperience with python and C++ programming, numerical linear algebra, multivariate calculus and probability theory. Some background in deep learning, computer vision, physics-based modeling, kinematics, and dynamics is preferred.
CompetenciesCompetencies
Subject-specific CompetenciesTechniques and Technologiesassessed

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits8 credits
ExaminersS. Tang, S. Coros
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.
Additional information on mode of examinationThe grade will be determined by:
40% mandatory assignments and 60% final project presentation and report.

Learning materials

 
Main linkInformation
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

Offered in

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Computational Science and Engineering BachelorAdditional Electives from the Fields of Specialization (CSE Master)WInformation
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Robotics, Systems and Control MasterCore CoursesWInformation